--- name: amazon-alexa description: "Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home)." risk: safe source: community date_added: '2026-03-06' author: renat tags: - voice - alexa - aws - smart-home - iot tools: - claude-code - antigravity - cursor - gemini-cli - codex-cli --- # AMAZON ALEXA — Voz Inteligente com Claude ## Overview Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home). ## When to Use This Skill - When you need specialized assistance with this domain ## Do Not Use This Skill When - The task is unrelated to amazon alexa - A simpler, more specific tool can handle the request - The user needs general-purpose assistance without domain expertise ## How It Works > Voce e o especialista em Alexa e AWS Voice. Missao: transformar > qualquer dispositivo Alexa em assistente ultra-inteligente usando > Claude como LLM backend, com voz neural, memoria persistente e > controle de Smart Home. Projeto-chave: AURI. --- ## 1. Visao Geral Do Ecossistema ``` [Alexa Device] → [Alexa Cloud] → [AWS Lambda] → [Claude API] Fala Transcricao Logica Inteligencia ↑ ↑ ↑ ↑ Usuario Intent Handler Anthropic + DynamoDB + Polly TTS + APL Visual ``` ## Componentes Da Arquitetura Auri | Componente | Servico AWS | Funcao | |-----------|-------------|--------| | Voz → Texto | Alexa ASR nativo | Reconhecimento de fala | | NLU | ASK Interaction Model + Lex V2 | Extrair intent e slots | | Backend | AWS Lambda (Python/Node.js) | Logica e orquestracao | | LLM | Claude API (Anthropic) | Inteligencia e respostas | | Persistencia | Amazon DynamoDB | Historico e preferencias | | Texto → Voz | Amazon Polly (neural) | Fala natural da Auri | | Interface Visual | APL (Alexa Presentation Language) | Telas em Echo Show | | Smart Home | Alexa Smart Home API | Controle de dispositivos | | Automacao | Alexa Routines API | Rotinas inteligentes | --- ## 2.1 Pre-Requisitos ```bash ## Ask Cli npm install -g ask-cli ask configure ## Aws Cli pip install awscli aws configure ``` ## Criar Skill Com Template ask new \ --template hello-world \ --skill-name auri \ --language pt-BR ## └── .Ask/Ask-Resources.Json ``` ## 2.3 Configurar Invocation Name No arquivo `models/pt-BR.json`: ```json { "interactionModel": { "languageModel": { "invocationName": "auri" } } } ``` --- ## 3.1 Intents Essenciais Para Auri ```json { "interactionModel": { "languageModel": { "invocationName": "auri", "intents": [ {"name": "AMAZON.HelpIntent"}, {"name": "AMAZON.StopIntent"}, {"name": "AMAZON.CancelIntent"}, {"name": "AMAZON.FallbackIntent"}, { "name": "ChatIntent", "slots": [{"name": "query", "type": "AMAZON.SearchQuery"}], "samples": [ "{query}", "me ajuda com {query}", "quero saber sobre {query}", "o que voce sabe sobre {query}", "explique {query}", "pesquise {query}" ] }, { "name": "SmartHomeIntent", "slots": [ {"name": "device", "type": "AMAZON.Room"}, {"name": "action", "type": "ActionType"} ], "samples": [ "{action} a {device}", "controla {device}", "acende {device}", "apaga {device}" ] }, { "name": "RoutineIntent", "slots": [{"name": "routine", "type": "RoutineType"}], "samples": [ "ativa rotina {routine}", "executa {routine}", "modo {routine}" ] } ], "types": [ { "name": "ActionType", "values": [ {"name": {"value": "liga", "synonyms": ["acende", "ativa", "liga"]}}, {"name": {"value": "desliga", "synonyms": ["apaga", "desativa", "desliga"]}} ] }, { "name": "RoutineType", "values": [ {"name": {"value": "bom dia", "synonyms": ["acordar", "manhã"]}}, {"name": {"value": "boa noite", "synonyms": ["dormir", "descansar"]}}, {"name": {"value": "trabalho", "synonyms": ["trabalhar", "foco"]}}, {"name": {"value": "sair", "synonyms": ["saindo", "goodbye"]}} ] } ] } } } ``` --- ## 4.1 Handler Principal Python ```python import os import time import anthropic import boto3 from ask_sdk_core.skill_builder import SkillBuilder from ask_sdk_core.handler_input import HandlerInput from ask_sdk_core.utils import is_intent_name, is_request_type from ask_sdk_model import Response from ask_sdk_dynamodb_persistence_adapter import DynamoDbPersistenceAdapter ## ============================================================ @sb.request_handler(can_handle_func=is_request_type("LaunchRequest")) def launch_handler(handler_input: HandlerInput) -> Response: attrs = handler_input.attributes_manager.persistent_attributes name = attrs.get("name", "") greeting = f"Oi{', ' + name if name else ''}! Eu sou a Auri. Como posso ajudar?" return (handler_input.response_builder .speak(greeting).ask("Em que posso ajudar?").response) @sb.request_handler(can_handle_func=is_intent_name("ChatIntent")) def chat_handler(handler_input: HandlerInput) -> Response: try: # Obter query slots = handler_input.request_envelope.request.intent.slots query = slots["query"].value if slots.get("query") else None if not query: return (handler_input.response_builder .speak("Pode repetir? Nao entendi bem.").ask("Pode repetir?").response) # Carregar historico attrs = handler_input.attributes_manager.persistent_attributes history = attrs.get("history", []) # Montar mensagens para Claude messages = history[-MAX_HISTORY:] messages.append({"role": "user", "content": query}) # Chamar Claude client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]) response = client.messages.create( model=CLAUDE_MODEL, max_tokens=512, system=AURI_SYSTEM_PROMPT, messages=messages ) reply = response.content[0].text # Truncar para nao exceder timeout if len(reply) > MAX_RESPONSE_CHARS: reply = reply[:MAX_RESPONSE_CHARS] + "... Quer que eu continue?" # Salvar historico history.append({"role": "user", "content": query}) history.append({"role": "assistant", "content": reply}) attrs["history"] = history[-50:] # Manter ultimas 50 handler_input.attributes_manager.persistent_attributes = attrs handler_input.attributes_manager.save_persist ## 4.2 Variaveis De Ambiente Lambda ``` ANTHROPIC_API_KEY=sk-... (armazenar em Secrets Manager) DYNAMODB_TABLE=auri-users AWS_REGION=us-east-1 ``` ## 4.3 Requirements.Txt ``` ask-sdk-core>=1.19.0 ask-sdk-dynamodb-persistence-adapter>=1.19.0 anthropic>=0.40.0 boto3>=1.34.0 ``` --- ## 5.1 Criar Tabela ```bash aws dynamodb create-table \ --table-name auri-users \ --attribute-definitions AttributeName=userId,AttributeType=S \ --key-schema AttributeName=userId,KeyType=HASH \ --billing-mode PAY_PER_REQUEST \ --region us-east-1 ``` ## 5.2 Schema Do Usuario ```json { "userId": "amzn1.ask.account.XXXXX", "name": "Joao", "history": [ {"role": "user", "content": "..."}, {"role": "assistant", "content": "..."} ], "preferences": { "language": "pt-BR", "voice": "Vitoria", "personality": "assistente profissional" }, "smartHome": { "devices": {}, "routines": {} }, "updatedAt": 1740960000, "ttl": 1748736000 } ``` ## 5.3 Ttl Automatico (Expirar Dados Antigos) ```python import time ## Adicionar Ttl De 180 Dias Ao Salvar attrs["ttl"] = int(time.time()) + (180 * 24 * 3600) ``` --- ## 6.1 Vozes Disponiveis (Portugues) | Voice | Idioma | Tipo | Recomendado | |-------|--------|------|-------------| | `Vitoria` | pt-BR | Neural | ✅ Auri PT-BR | | `Camila` | pt-BR | Neural | Alternativa | | `Ricardo` | pt-BR | Standard | Masculino | | `Ines` | pt-PT | Neural | Portugal | ## 6.2 Integrar Polly Na Resposta ```python import boto3 import base64 def synthesize_polly(text: str, voice_id: str = "Vitoria") -> str: """Retorna URL de audio Polly para usar em Alexa.""" client = boto3.client("polly", region_name="us-east-1") response = client.synthesize_speech( Text=text, OutputFormat="mp3", VoiceId=voice_id, Engine="neural" ) # Salvar em S3 e retornar URL # (necessario para usar audio customizado no Alexa) return upload_to_s3(response["AudioStream"].read()) def speak_with_polly(handler_input, text, voice_id="Vitoria"): """Retornar resposta usando voz Polly customizada via SSML.""" audio_url = synthesize_polly(text, voice_id) ssml = f'

' return handler_input.response_builder.speak(ssml) ``` ## 6.3 Ssml Para Controle De Voz ```xml Oi! Eu sou a Auri. Como posso ajudar? ``` --- ## 7.1 Template De Chat ```json { "type": "APL", "version": "2023.3", "theme": "dark", "mainTemplate": { "parameters": ["payload"], "items": [{ "type": "Container", "width": "100%", "height": "100%", "backgroundColor": "#1a1a2e", "items": [ { "type": "Text", "text": "AURI", "fontSize": "32px", "color": "#e94560", "textAlign": "center", "paddingTop": "20px" }, { "type": "Text", "text": "${payload.lastResponse}", "fontSize": "24px", "color": "#ffffff", "padding": "20px", "maxLines": 8, "grow": 1 }, { "type": "Text", "text": "Diga algo para continuar...", "fontSize": "18px", "color": "#888888", "textAlign": "center", "paddingBottom": "20px" } ] }] } } ``` ## 7.2 Adicionar Apl Na Resposta ```python @sb.request_handler(can_handle_func=is_intent_name("ChatIntent")) def chat_with_apl(handler_input: HandlerInput) -> Response: # ... obter reply do Claude ... # Verificar se device suporta APL supported = handler_input.request_envelope.context.system.device.supported_interfaces has_apl = getattr(supported, "alexa_presentation_apl", None) is not None if has_apl: apl_directive = { "type": "Alexa.Presentation.APL.RenderDocument", "token": "auri-chat", "document": CHAT_APL_DOCUMENT, "datasources": {"payload": {"lastResponse": reply}} } handler_input.response_builder.add_directive(apl_directive) return handler_input.response_builder.speak(reply).ask("Mais alguma coisa?").response ``` --- ## 8.1 Ativar Smart Home Skill No `skill.json`, adicionar: ```json { "apis": { "smartHome": { "endpoint": { "uri": "arn:aws:lambda:us-east-1:123456789:function:auri-smart-home" } } } } ``` ## 8.2 Handler De Smart Home ```python def handle_smart_home_directive(event, context): namespace = event["directive"]["header"]["namespace"] name = event["directive"]["header"]["name"] endpoint_id = event["directive"]["endpoint"]["endpointId"] if namespace == "Alexa.PowerController": state = "ON" if name == "TurnOn" else "OFF" # Chamar sua API de smart home control_device(endpoint_id, {"power": state}) return build_smart_home_response(endpoint_id, "powerState", state) elif namespace == "Alexa.BrightnessController": brightness = event["directive"]["payload"]["brightness"] control_device(endpoint_id, {"brightness": brightness}) return build_smart_home_response(endpoint_id, "brightness", brightness) ``` ## 8.3 Discovery De Dispositivos ```python def handle_discovery(event, context): return { "event": { "header": { "namespace": "Alexa.Discovery", "name": "Discover.Response", "payloadVersion": "3" }, "payload": { "endpoints": [ { "endpointId": "light-sala-001", "friendlyName": "Luz da Sala", "displayCategories": ["LIGHT"], "capabilities": [ { "type": "AlexaInterface", "interface": "Alexa.PowerController", "version": "3" }, { "type": "AlexaInterface", "interface": "Alexa.BrightnessController", "version": "3" } ] } ] } } } ``` --- ## Deploy Completo (Skill + Lambda) cd auri/ ask deploy ## Verificar Status ask status ## Testar No Simulador ask dialog --locale pt-BR ## Teste Especifico De Intent ask simulate \ --text "abrir auri" \ --locale pt-BR \ --skill-id amzn1.ask.skill.YOUR-SKILL-ID ``` ## Criar Lambda Manualmente aws lambda create-function \ --function-name auri-skill \ --runtime python3.11 \ --role arn:aws:iam::ACCOUNT:role/auri-lambda-role \ --handler lambda_function.handler \ --timeout 8 \ --memory-size 512 \ --zip-file fileb://function.zip ## Adicionar Trigger Alexa aws lambda add-permission \ --function-name auri-skill \ --statement-id alexa-skill-trigger \ --action lambda:InvokeFunction \ --principal alexa-appkit.amazon.com \ --event-source-token amzn1.ask.skill.YOUR-SKILL-ID ``` ## Usar Secrets Manager aws secretsmanager create-secret \ --name auri/anthropic-key \ --secret-string '{"ANTHROPIC_API_KEY": "sk-..."}' ## Lambda Acessa Via Sdk: import boto3, json def get_secret(secret_name): client = boto3.client('secretsmanager') response = client.get_secret_value(SecretId=secret_name) return json.loads(response['SecretString']) ``` --- ## Fase 1 — Setup (Dia 1) ``` [ ] Conta Amazon Developer criada [ ] Conta AWS configurada (free tier) [ ] ASK CLI instalado e configurado [ ] IAM Role criada com permissoes: Lambda, DynamoDB, Polly, Logs [ ] Anthropic API key armazenada em Secrets Manager ``` ## Fase 2 — Skill Base (Dia 2-3) ``` [ ] ask new --template hello-world --skill-name auri [ ] Interaction model definido (pt-BR.json) [ ] LaunchRequest handler funcionando [ ] ChatIntent handler com Claude integrado [ ] ask deploy funcionando [ ] Teste basico no ASK simulator ``` ## Fase 3 — Persistencia (Dia 4) ``` [ ] DynamoDB table criada [ ] Persistencia de historico funcionando [ ] TTL configurado [ ] Preferencias do usuario salvas ``` ## Fase 4 — Polly + Apl (Dia 5-6) ``` [ ] Polly integrado com voz Vitoria (neural) [ ] APL template de chat criado [ ] APL renderizando em Echo Show simulator ``` ## Fase 5 — Smart Home (Opcional) ``` [ ] Smart Home skill habilitada [ ] Discovery de dispositivos funcionando [ ] PowerController implementado [ ] Teste com device real ``` ## Fase 6 — Publicacao ``` [ ] Teste completo de todas funcionalidades [ ] Performance OK (< 8s timeout) [ ] Certificacao Amazon submetida [ ] Publicado na Alexa Skills Store ``` --- ## 11. Comandos Rapidos | Acao | Comando | |------|---------| | Criar skill | `ask new --template hello-world` | | Deploy | `ask deploy` | | Simular | `ask simulate --text "abre a auri"` | | Dialog interativo | `ask dialog --locale pt-BR` | | Ver logs | `ask smapi get-skill-simulation` | | Validar modelo | `ask validate --locales pt-BR` | | Exportar skill | `ask smapi export-package --skill-id ID` | | Listar skills | `ask list skills` | --- ## 12. Referencias - Boilerplate Python completo: `assets/boilerplate/lambda_function.py` - Interaction model PT-BR: `assets/interaction-models/pt-BR.json` - APL chat template: `assets/apl-templates/chat-interface.json` - Smart Home examples: `references/smart-home-api.md` - ASK SDK Python docs: https://github.com/alexa/alexa-skills-kit-sdk-for-python - Claude + Alexa guide: https://www.anthropic.com/news/claude-and-alexa-plus ## Best Practices - Provide clear, specific context about your project and requirements - Review all suggestions before applying them to production code - Combine with other complementary skills for comprehensive analysis ## Common Pitfalls - Using this skill for tasks outside its domain expertise - Applying recommendations without understanding your specific context - Not providing enough project context for accurate analysis ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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